What is cluster sampling?

Cluster sampling is a sampling method in which a population is divided into groups from which random samples are taken for observation. This method is used when it is difficult to obtain a complete population member list, but a complete list of grouped population clusters is available.

The group being sampled within a cluster should ideally be heterogeneous but with a relatively similar cluster mean. Cluster sampling should focus on groups that accurately represent the larger population. Depending on what data points are being observed, cluster sampling sometimes obtains location-specific information by dividing populations into groups based on their geographical distribution.